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Sidhant Narula

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#artificial intelligence Preprint Oct 2026

COPEX: Benchmarking LLM Robustness to Adversarial Context Across Model Context Protocol Layers

Large language models increasingly mediate tool use in Model Context Protocol (MCP) systems, where adversarial influence may enter through user instructions, tool schemas, tool outputs, or protocol messages. Existing benchmarks often evaluate deployed agents, conflating model susceptibility with guardrails, orchestrati...

Nahom Birhan, Mehrdad Rostamzadeh, Sidhant Narula et al. · 0 citations
Preprint Aug 2026

TrustShiftProbe: Characterizing, Benchmarking, and Defending Staged Trust Attacks on MCP Servers

TrustShiftProbe is introduced, an evaluation and defense framework with four contributions: a stateful temporal threat model of the agent-server lifecycle as a benign conditioning phase followed by an adversarial defection at a trust horizon, and a language-agnostic attack engine that instantiates each variant as a com...

Mehrdad Rostamzadeh, Sidhant Narula, Mohammad GhasemiGol et al. · 1 citation

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